1. Field of the Invention
The present invention relates generally to a method and apparatus for reducing the coding artifacts which appear in images which are encoded by block-based and/or object-based encoding.
2. Description of the Related Art
In image encoding methods which are based either on block-based transformation encoding or on object-based transformation encoding, digitized images are divided into blocks or objects, respectively, and each block or object is sequentially encoded independently of neighboring blocks or objects. Coding errors which disturb the image and which are referred to as coding artifacts may arise, particularly at high compression factors, due to the independent encoding of the image blocks or image objects. An example of a coding artifact may be seen in the formation of the artificial edge at the block margin in what is referred to as a block artifact, or in the ring-like patterns at gray scale discontinuities in what is referred to as ringing in the encoded image. For a viewer of an image which has been encoded and decoded with an image encoding method based on one of the above-described principles, the encoding errors leads to a noticeable deterioration in the subjective quality of the decoded image which increases with increasing compression of the image data.
Various methods are known which are based on the principle of block-based transformation encoding. The following image encoding methods are a selection of block-based image encoding processes:
JPEG; PA1 MPEG 1, MPEG 2, or PA1 H.263.
Object-based image encoding methods are also known.
A method of block-based image encoding is known which also utilizes the framework of an object-based image encoding method.
Two fundamental approaches have been used for reducing the coding errors which occur under the boundary condition of the compatibility of the known image encoding methods. First, an arrangement and a method are known with which a decoded image is made smoother by a low-pass filter which follows the decoding apparatus, wherein the low-pass filter that is used may be a global filter or a local adaptive filter. A considerable disadvantage in this method is that not only does the filtering remove artificial gray scale discontinuities at the block margins as intended but it also causes an undesirable smoothing of the high-frequency details within the image so that the viewer perceives the details as being of only poor quality or perhaps does not see the details at all.
To avoid the undesired smoothing of important details in the image, the low-pass filtering operation may be limited to the block margins. Such a method is known although it has disadvantages in that what are referred to as ringing effects that are typically distributed over the entire image block cannot be eliminated.
According to another process, the image enhancement is implemented on the basis of prior knowledge about the encoded image. In this method, the decoding process is not the simple inversion of the transmission-side encoding but instead is carried out as an optimization problem. The receiving side thus determines that the image conforms to the received, quantized image data on one hand, but also meets certain boundary conditions of typical image data such as, for example, smoothness, on the other hand. This procedure has the disadvantage that the method requires extremely high complexity and the boundary conditions are formulated both in the time domain as well as in the frequency domain and a constant change between the domains is required in the image enhancement process. It is not possible to provide a real-time realization of this method in video communications.
A known image enhancement method is implemented so that a new brightness value or color value is determined for a picture element of an image and is allocated to the picture element, the brightness and/or color value being determined from a determination of the old, decoded brightness value or color value of the picture element and directly from the neighboring picture elements.
There are particular disadvantages to this method in that, independently of the semantics of the image, all the neighboring picture elements are taking into consideration in the averaging of the brightness values or color values. The semantics of the image here means the size of the difference in the brightness values of neighboring picture elements or whether two picture elements are located in different image blocks of different objects. This method leads to a slight image enhancement in the decoding of the digitized image.